---
title: "20CSEG06"
author: "DINESH RAJAN R A"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    social: ["twitter","facebook","menu"]
    source_code: embed
---

```{r setup, include=FALSE}
library(flexdashboard)
library(knitr)
library(DT)
library(rpivotTable)
library(ggplot2)
library(plotly)
library(dplyr)
library(openintro)
library(ggvis)
library(MASS)
```

```{r}
data(quine)
```

```{r}
mycolors=c("blue","#FFC125","darkgreen","darkorange")
```

Interactive Data Visualization
=====================================

Row
-------------------------------------

### Absent Record Analysis

```{r}
valueBox(paste("Days"),
         color = "warning")
```

### Absent by Age Group

```{r}
valueBox(length(quine$Age),
         icon = "fa-user")
```

### AVg Absent by age group

```{r}
gauge(round(mean(quine$Age),
            digits = 2),
            min = 0,
            max = 350,
            gaugeSectors(success = c(0, 150),
                         warning = c(150, 240),
                         danger = c(240, 350),
                         colors = c("green", "yellow", "red")))
```



### F0
```{r}
valueBox(sum(quine$Age == "F0"),
         icon = 'fa-building')
```

### F1
```{r}
valueBox(sum(quine$Age == "F1"),
         icon = 'fa-building')
```

### F2
```{r}
valueBox(sum(quine$Age == "F2"),
         icon = 'fa-building')
```

### F3
```{r}
valueBox(sum(quine$Age == "F3"),
         icon = 'fa-building')
```

Row
-------------------------------

### Absent by Age Group

```{r}
d2=quine %>%
         group_by(Age) %>%
         summarise(Days = n()) %>%
         plot_ly(x = ~Age,
                 y = ~Days,
                 color = "blue",
                 type = 'bar') %>%
layout(xaxis = list(title = "Absent By Age Group"),
yaxis = list(title = 'Days'))
d2
```

### Most Absent by Age Group

```{r}
d3=quine %>%
         group_by(Age) %>%
         summarise(Days = n()) %>%
         filter(Days>18) %>%
         plot_ly(labels = ~Age,
                 values = ~Days,
                 marker = list(colors = mycolors)) %>%
         add_pie(hole = 0.2) %>%
         layout(xaxis = list(zeroline = F,
                             showline = F,
                             showticklabels = F,
                             showgrid = F),
                yaxis = list(zeroline = F,
                             showline = F,
                             showticklabels=F,
                             showgrid=F))
d3
```

### lrn vs Days

```{r}
d4=plot_ly(quine,
              x = ~Lrn,
              y = ~Days,
              text = paste("Lrn:", quine$Lrn,
                           "Days:",
                           quine$Days),
              type = "bar") %>%
         layout(xaxis = list(title="Lrn"),
                yaxis = list(title = "Lrn vs Days"))
d4
```

Row
------------------------------------

### boxplot for most absent in days
```{r}
quine %>%
         group_by(Age) %>%
         ggvis(~Age, ~Days, fill = ~Age) %>%
         layer_boxplots()
```

Data Table
========================================

```{r}
datatable(quine,
          caption = "Absent Data",
          rownames = T,
          filter = "top",
          options = list(pageLength = 25))

```

Pivot Table
=========================================

```{r}
rpivotTable(quine,
            aggregatorName = "Count",
            cols= "Days",
            rows = "Age",
            rendererName = "Heatmap")

```

Summary {data-orientation=columns} 
===========================================

Column 
-----------------------------------

### Max Absent Days

```{r}
valueBox(max(quine$Days),
         icon = "fa-user" )
```

### Average Absent Days
```{r}
valueBox(round(mean(quine$Days),
               digits = 2),
         icon = "fa-area-chart")
```

Column
---------------------------

Report

* This is a report on `r length(quine$Days)` days of observation of students absenteeism.

* The average absent days `r mean(quine$Days)`.

This report was generated on `r format(Sys.Date(), format = "%B %d, %Y")`.

About Report
========================================

Created by: DINESH RAJAN R A

Confidential: HIGHLY!